High performance plasma-assisted etch processes are important to the success of many semiconductor processing workflows. However, monitoring, controlling, and/or optimizing the etch processes can be difficult and time-consuming, oftentimes involving process engineers laboriously testing etch process parameters to empirically determine settings that produce a target etch profile. Additionally, in situ monitoring of etch processes can be difficult and unreliable; etch endpoint detection remains a challenge.
Computational models might be useful to facilitate designing and monitoring etch processes. Some models attempt to simulate the physical-chemical processes occurring on semiconductor substrate surfaces during etch processes. Examples include the etch profile models of M. Kushner and co-workers as well as the etch profile models of Cooperberg and co-workers. The former are described in Y. Zhang, “Low Temperature Plasma Etching Control through Ion Energy Angular Distribution and 3-Dimensional Profile Simulation,” Chapter 3, dissertation, University of Michigan (2015), and the latter in Cooperberg, Vahedi, and Gottscho, “Semiempirical profile simulation of aluminum etching in a Cl2/BCl3 plasma,” J. Vac. Sci. Technol. A 20(5), 1536 (2002), each of which is hereby incorporated by reference in its entirety for all purposes. Additional description of the etch profile models of M. Kushner and co-workers may be found in J. Vac. Sci. Technol. A 15(4), 1913 (1997), J. Vac. Sci. Technol. B 16(4), 2102 (1998), J. Vac. Sci. Technol. A 16(6), 3274 (1998), J. Vac. Sci. Technol. A 19(2), 524 (2001), J. Vac. Sci. Technol. A 22(4), 1242 (2004), J. Appl. Phys. 97, 023307 (2005), each of which is also hereby incorporated by reference in its entirety for all purposes. Despite the extensive work done to develop these models, they do not yet possess the desired degree of accuracy and reliability to find substantial use within the semiconductor processing industry.